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dc.contributor.authorGilbert, Benoiten_US
dc.contributor.authorTeh, L. H.en_US
dc.contributor.authorGuan, Hongen_US
dc.date.accessioned2012-05-18en_US
dc.date.accessioned2013-02-08T02:08:35Z
dc.date.accessioned2017-03-01T22:44:11Z
dc.date.available2017-03-01T22:44:11Z
dc.date.issued2012en_US
dc.date.modified2013-02-08T02:08:35Z
dc.identifier.isbnorissn1839-292Xen_US
dc.identifier.urihttp://hdl.handle.net/10072/49041
dc.description.abstractFor economical benefits, optimisation of mass-produced structural steel products is widely researched. The objective is to minimise the quantity of material used without sacrificing the strength and practicality of the structural members. Current research focuses on optimising the dimensions of conventional cross-sectional shapes but rarely considers discovering new optimum shapes. This report introduces the concepts of a new optimisation method which enables the cross-section to self-shape to an optimum by using the evolution and adaptation benefits of Genetic Algorithm. The feasibility and accuracy of the method are verified by implementing it to find optimum thin-walled profiles against simple parameters for which analytical solutions are known, namely the optimisation of doubly-symmetric closed profiles. Results show that the cross-section accurately self-shapes to its optimum in a low number of generations. Factors influencing the convergence are presented and future challenges to applying the method to optimisation of cold-formed steel profiles with practical applications are discussed.en_US
dc.description.peerreviewedNoen_US
dc.description.publicationstatusYesen_US
dc.format.extent1122490 bytes
dc.format.mimetypeapplication/pdf
dc.publisherCentre for Infrastructure Engineering and Managementen_US
dc.publisher.placeGold Coast, Australiaen_US
dc.publisher.urihttp://www.griffith.edu.au/en_US
dc.relation.ispartofbookorjournalCentre for Infrastructure Engineering and Management, Research Report CIEM/2011/R01en_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofpagefrom1en_US
dc.relation.ispartofpageto27en_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchStructural Engineeringen_US
dc.subject.fieldofresearchcode090506en_US
dc.titleSelf-shape optimisation of cold-formed steel closed profiles using Genetic Algorithmen_US
dc.typeReport
dc.type.descriptionMajor Reviews/Reportsen_US
dc.type.codeden_US
gro.facultyFaculty of Science, Environment, Engineering and Technologyen_US
gro.rights.copyright© 2012 Centre for Infrastructure Engineering and Management. This publication may be redistributed freely in its entirety and in its original form without the consent of the copyright owner. Use of material contained in this publication in any other published works must be appropriately referenced, and, if necessary, permission sought from the author.en_US
gro.date.issued2012
gro.hasfulltextFull Text
gro.griffith.authorGilbert, Benoit
gro.griffith.authorGuan, Hong


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